from typing import Optional

from fastapi.openapi.models import OpenIdConnect as OpenIdConnectModel
from fastapi.security.base import SecurityBase
from starlette.exceptions import HTTPException
from starlette.requests import Request
from starlette.status import HTTP_403_FORBIDDEN
from typing_extensions import Annotated, Doc


class OpenIdConnect(SecurityBase):
    """
    OpenID Connect authentication class. An instance of it would be used as a

```Python hl_lines="1  10-13  21-24"
{!../../docs_src/sql_databases/sql_app/models.py!}
```

### ✍ 💛

🔜 ✍ 💛.

👉, 👥 ⚙️ `relationship` 🚚 🇸🇲 🐜.

👉 🔜 ▶️️, 🌅 ⚖️ 🌘, "🎱" 🔢 👈 🔜 🔌 💲 ⚪️➡️ 🎏 🏓 🔗 👉 1️⃣.

```Python hl_lines="2  15  26"
{!../../docs_src/sql_databases/sql_app/models.py!}
```

specific language governing permissions and limitations
under the License.
-->

<model xmlns="http://codehaus-plexus.github.io/MODELLO/2.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xsi:schemaLocation="http://codehaus-plexus.github.io/MODELLO/2.0.0 https://codehaus-plexus.github.io/modello/xsd/modello-2.0.0.xsd"
  xml.namespace="http://maven.apache.org/LIFECYCLE/${version}"

from fastapi.openapi.models import SecurityBase as SecurityBaseModel


class SecurityBase:
    model: SecurityBaseModel

    "functionalTests": true,
    "crossVersionTests": false
  },
  {
    "name": "model-core",
    "path": "platforms/core-configuration/model-core",
    "unitTests": true,
    "functionalTests": true,
    "crossVersionTests": false
  },
  {
    "name": "model-groovy",
    "path": "platforms/core-configuration/model-groovy",
    "unitTests": true,
    "functionalTests": true,
    "crossVersionTests": false

# Build state model

The Gradle daemon tracks state for various elements. These are arranged in a hierarchy:

```mermaid
  graph TD

  process["build process"]
  
  session["build session"]
  process --> session
  
  build_tree["build tree"]
  session --> build_tree
  
  build1["root build"]
  build_tree --> build1
  
  project1["root project"]
  build1 --> project1
  
  project2["project"]
  build1 --> project2

~~ under the License.

 -----
 Super POM
 -----
 Hervé Boutemy
 -----
 2011-09-12
 -----

Super POM

 All models implicitly inherit from a super-POM:

* Autenticação **Token JWT**.
* Modelos **SQLAlchemy** (independente de extensões Flask, para que eles possam ser usados com _workers_ Celery diretamente).
* Modelos básicos para usuários (modifique e remova conforme suas necessidades).
* Migrações **Alembic**.
* **CORS** (_Cross Origin Resource Sharing_ - Compartilhamento de Recursos Entre Origens).
* _Worker_ **Celery** que pode importar e usar modelos e códigos do resto do _backend_ seletivamente.

    return x * 42


ml_models = {}


@asynccontextmanager
async def lifespan(app: FastAPI):
    # Load the ML model
    ml_models["answer_to_everything"] = fake_answer_to_everything_ml_model
    yield
    # Clean up the ML models and release the resources
    ml_models.clear()


app = FastAPI(lifespan=lifespan)


@app.get("/predict")
async def predict(x: float):

### Create the `Settings` object

Import `BaseSettings` from Pydantic and create a sub-class, very much like with a Pydantic model.

The same way as with Pydantic models, you declare class attributes with type annotations, and possibly default values.

You can use all the same validation features and tools you use for Pydantic models, like different data types and additional validations with `Field()`.

//// tab | Pydantic v2